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# -*- coding: utf-8 -*-
"""
Created on Wed Jan 13 19:36:37 2016
@author: Junfu Pu, pjh@mail.ustc.edu.cn
Algorithm for CaptchaLess
"""
importImage
importnumpyasnp
fromosimportlistdir
importos
importscipy
classYJS_EPC:
def__getTemplate_yjs(self):
im1=Image.open('Template_yjs_epc/0130')
im2=Image.open('Template_yjs_epc/3214')
im3=Image.open('Template_yjs_epc/7564')
im4=Image.open('Template_yjs_epc/7849')
bw_im1=np.array(im1.convert('L'))>128
bw_im2=np.array(im2.convert('L'))>128
bw_im3=np.array(im3.convert('L'))>128
bw_im4=np.array(im4.convert('L'))>128
dic_0=bw_im1[:,0:10].copy()
dic_1=bw_im1[:,10:20].copy()
dic_2=bw_im2[:,10:20].copy()
dic_3=bw_im2[:,0:10].copy()
dic_4=bw_im2[:,30:40].copy()
dic_5=bw_im3[:,10:20].copy()
dic_6=bw_im3[:,20:30].copy()
dic_7=bw_im3[:,0:10].copy()
dic_8=bw_im4[:,10:20].copy()
dic_9=bw_im4[:,30:40].copy()
Dict= [dic_0,dic_1,dic_2,dic_3,dic_4,dic_5,dic_6,dic_7,dic_8,dic_9]
returnDict
defmakePrediction_yjs(self, img_test):
Dict=self.__getTemplate_yjs()
dist=np.zeros((10,4))
img_test=np.array(img_test.convert('L'))>128
foriinrange(4):
subImg=img_test[:,i*10:(i+1)*10]
j=0
fordicinDict:
dist[j,i] = (dic^subImg).sum()
j+=1
result=dist.argmin(axis=0)
checkcode=''.join([str(e) foreinresult])
returncheckcode
classMIS:
def__getTemplate_mis(self):
Names_num= ['2.npy','3.npy','4.npy','5.npy','6.npy', \
'7.npy','8.npy','9.npy']
Names_alp= []
foriinrange(65,91):
Names_alp.append(chr(i)+'.npy')
Names_alp.remove('I.npy')
Dict= []
label= []
i=2
fornameinNames_num:
img=np.load('Template_mis/'+name)
# bw_img = np.array(img.convert('L'))>128
bw_img=img
Dict.append(bw_img)
label.append(str(i))
i+=1
foriinrange(65,91):
label.append(chr(i))
label.remove('I')
fornameinNames_alp:
img=np.load('Template_mis/'+name)
# bw_img = np.array(img.convert('L'))>128
bw_img=img
Dict.append(bw_img)
return (Dict,label)
defmakePrediction_mis(self, img_test):
(Dict,label) =self.__getTemplate_mis()
dist=np.zeros((33,4))
# img_test = np.array(img_test.convert("L"))>128
foriinrange(4):
subImage=img_test[i]
j=0
fordictinDict:
d=np.zeros(10)
forkinrange(10):
subTemplate=dict[k:20+k,:]
d[k] = (subTemplate^subImage).sum()
dist[j,i] =d.min()
j+=1
result_index=dist.argmin(axis=0)
result= []
forresinresult_index:
result.append(label[res])
checkcode=''.join([str(e) foreinresult])
returncheckcode
defmakePrediction_mis_test(self, img_test):
(Dict,label) =self.__getTemplate_mis()
result= []
foriinrange(4):
subImg=img_test[i]
result.append(self.makePrediction_mis_single(subImg, Dict, label))
checkcode=''.join(result)
returncheckcode
defmakePrediction_mis_single(self, subImage, Dict, label):
testFeat=self.__getFeature(subImage)
dist=np.zeros(33)
foriinrange(33):
tempImg=Dict[i]
tempFeat=self.__getFeature(tempImg)
dist[i] = ((tempFeat-testFeat)**2).sum()
result_index=dist.argmin()
result=str(label[result_index])
returnresult
def__getFeature(self, img):
nR=5;
nC=4;
(r, c) =img.shape
deltaR=r/nR
deltaC=c/nC
hist=np.zeros((nR, nC))
foriinrange(nR):
forjinrange(nC):
block=img[i*deltaR:(i+1)*deltaR, j*deltaC:(j+1)*deltaC]
hist[i,j] =block.sum()
feat=hist.reshape(nR*nC)
feat=feat/(float(feat.sum())+1)
returnfeat
defget_narrowest(self, im_array):
min_width=20
min_angle=0
im_standrad=None
min_word_left=0
min_word_right=20
# rotate the image and get the smallest width,treat the image at that time as template
forangleinrange(-90, 90, 1):
#im_array is bool array, cannot convert to image directly
im_array_int=im_array.astype(np.uint8)
im=Image.fromarray(im_array_int)
im_tmp=np.array(im.rotate(angle).convert('L'))
[width, word_left, word_right] =self.get_width(im_tmp)
if (width<min_width):
min_width=width
min_angle=angle
im_standrad=im_tmp
min_word_left=word_left
min_word_right=word_right
return [im_standrad, min_width, min_angle, min_word_left, min_word_right];
# def generate_template(self, code_name, im_array):
#
# [im_standrad, min_width, angle, min_word_left, min_word_right] = self.get_narrowest(im_array)
#
# # use an array of 30x20 to contain word
# bg = np.zeros(shape=(30,20), dtype = np.bool)
# bg.dtype= "bool_"
# bg[5:25, (20 - min_width)/2-2:(20 - min_width)/2 + min_width+2] = im_standrad[0:20, min_word_left-2:min_word_right+2]
# np.save("./codes_template/"+code_name, bg)
# f=open(code_name+'.jpg', 'wb')
# bg.dtype="int"
# f.write(bg)
# f.close()
# get the width of word in image array
defget_width(self, im_array):
word_left=0
word_right=20
forxinrange(0, 20):
col_sum=im_array[:, x].sum()
ifcol_sum>0:
# print('word begin:', x)
word_left=x
break
forxinreversed(range(20)):
col_sum=im_array[:, x].sum()
ifcol_sum>0:
# print('word end:', x)
word_right=x
break
return [word_right-word_left, word_left, word_right]
defsplit_codes(self, checkcode):
codes= []
foriinrange(4):
box= [20*i, 0, 20*(i+1), 20]
code=checkcode.crop(box)
code_array=np.array(code.convert('L')) <128
[narrowest_code_array,a,b,c,d] =self.get_narrowest(code_array)
codes.append(narrowest_code_array)
#plt.imshow(narrowest_code_array, cmap="Greys")
#plt.show()
returncodes